Channel estimation method and apparatus determining a channel impulse response (cir) distribution area using two adjacent windows

ABSTRACT

A channel estimation method and apparatus based on two adjacent windows. The channel estimation method includes scanning a signal containing noise and channel impulse response (CIR) information with a first window and a second window, detecting a CIR distribution area based on the ratio between the average power of the signal within the first window and the average power of the signal within the second window and at least one threshold value, eliminating the noise from the CIR distribution area and estimating the CIR information. Accordingly, noise interference can be minimized and accurate channel estimation can be accomplished.

CROSS-REFERENCE TO RELATED PATENT APPLICATION

This application claims priority under 35 U.S.C. § 119 rom Korean PatentApplication No. 10-2006-0123523, filed on Dec. 7, 2006, the disclosureof which is hereby incorporated by reference herein as if set forth inits entirety.

FIELD OF THE INVENTION

The present invention relates to an orthogonal frequency divisionmultiplexing (OFDM) communication system, and more particularly, to achannel estimation method and apparatus for determining a channelimpulse response (CIR) distribution based on characteristics of twoadjacent signal windows in a receiver in an orthogonal frequencydivision multiplexing (OFDM) communication system.

BACKGROUND OF THE INVENTION

Orthogonal frequency division multiplexing (OFDM) is a widebandmodulation scheme in which a frequency bandwidth allocated for acommunication session is divided into a plurality of narrow bandfrequency sub-bandwidths. Each narrow band frequency sub-bandwidthincludes a radio frequency (RE) subcarrier. Subcarriers in differentsub-channels are mathematically orthogonal to each other.

OFDM is a multi-carrier modulation scheme involving converting data tobe transmitted into an M-ary quadrature amplitude modulation (QAM)complex symbol, converting a complex symbol sequence into a plurality ofparallel complex symbols through serial-to-parallel conversion, andperforming rectangular pulse shaping and subcarrier modulation of eachparallel complex symbol. In the multi-carrier modulation, a frequencyinterval between subcarriers is set such that all of the subcarriermodulated parallel complex symbols are orthogonal to each other.Accordingly, OFDM allows the individual spectrums of subcarriers tooverlap without inter-carrier-interference (ICI). This is due to theorthogonality of the subcarriers and also allows a high datatransmission rate and high bandwidth use efficiency since a frequencybandwidth is divided into a plurality of orthogonal sub-bandwidths.

In data transmission systems (e.g., cyclic prefix (CP)-OFDM or timedomain synchronous (TDS)-OFDM systems) using OFDM, a receiver identifiesthe characteristics of a channel by estimating a channel impulseresponse (CIR) while estimating the channel based on a known data signaltransmitted from a transmitter. However, in addition to the transmittedinformation used to estimate the CIR, the received signal may alsoinclude noise such as adjacent channel interference or white Gaussiannoise, which may make channel estimation difficult.

FIGS. 1A through 1C are graphs illustrating received OFDM signalsincluding noise and CIR information. FIG. 1A is a graph illustrating theamplitude of a CIR in a TU6 channel model, which is disclosed in “COST207 TD(86)51-REW3(WG1): Proposal on Channel Transfer Functions to beUsed in GSM Tests Late 1986, September 1986”. Referring to FIG. 1A, sixchannel paths exist in an exemplary channel (channel model) in terms ofcontinuous time. FIG. 1B illustrates CIRs existing within a time period,during which no pulse exists in the channel model illustrated in FIG.1A. These CIRs are unwanted CIR components having a low-energy value andare generated due to energy leakage from a period in which pulses exist.FIG. 1C is a graph obtained by observing the CIRs illustrated in FIG. 1Bin terms of time variation. It can be determine from the graph that CIRsexist within the period in which no pulse exist in the channel modelillustrated in FIG. 1A.

The above-mentioned CIRs being unwanted CIR components having alow-energy value may make it difficult to detect a CIR based on a knowntransmission signal generated by an OFDM transmitter. For instance, evenif the method of threshold detection disclosed in “Z. Yang, J. Wang, C.Pan, et al., “Channel Estimation of DMB-T,” in 2002 IEEE Conf. Commu.,Circuits and Systems and West Sino Expositions, pp. 1069-1072” is used,CIR detection may be difficult due to an unwanted CIR component, havinga low-energy value because of inter-symbol interference (ISI) having ahigh-energy value and energy leakage in a channel model.

SUMMARY OF THE INVENTION

Various embodiments of the present invention provide a channelestimation method and apparatus in which a channel impulse response(CIR) distribution area is subdivided during CIR estimation andminimizing noise interference and accurately estimating a channel.

According to some embodiments of the present invention, there isprovided a channel estimation method including detecting a CIRdistribution area by scanning a signal containing noise and CIRinformation with a first window and a second window adjacent to thefirst window, by calculating a ratio between an average power of thefirst window and an average power of the second window, by comparing thecalculated average power ratio with at least one threshold value, and bycalculating a start point, at which the average power ratio is initiallyequal to the at least one threshold value, and an end point, at whichthe average power ratio is lastly equal to the at least one thresholdvalue; and eliminating the noise from the CIR distribution area andestimating the CIR information.

Detecting the CIR distribution area may include scanning the firstwindow and the second window by a predetermined step interval repeatedlyand calculating the average power of the first window and the averagepower of the second window according to corresponding step; calculatinga first ratio of the average power of the second window to the averagepower of the first window and a second ratio of the average power of thefirst window to the average power of the second window according to thecorresponding step; comparing the first ratio with a first thresholdvalue and detecting the start point, at which the first ratio isinitially equal to the first threshold value, based on a result of thecomparison; and comparing the second ratio with a second threshold valueand detecting the end point, at which the second ratio is lastly equalto the second threshold value. based on a result of the comparison.

The first ratio may have characteristics of F distribution, the firstthreshold value may correspond to a value corresponding to F_(β)(D_(l),D_(r)) in an F distribution table, the second ratio may have thecharacteristics of the F distribution, the second threshold value maycorrespond to a value corresponding to F_(β)(D_(r), D_(l)) in the Fdistribution table, Here, β is be a false detection probability, D_(l)is a length of the first window, and D_(r) is a length of the secondwindow.

Before detecting the CIR distribution area, the channel estimationmethod may further include eliminating other noise from the signal,which contains the noise and the CIR information>and estimating the CIRinformation.

The channel estimation method may be recorded as a program in a computerreadable medium.

According to other embodiments of the present invention, there isprovided a channel estimation apparatus including a linear correlatorconfigured to receive a baseband sample complex signal and a localpseudo-noise (PN) signal and to generate a correlation signal bycalculating a linear correlation between the two signals; and a CIRestimator configured to receive the correlation signal, to eliminatenoise from the correlation signal, to perform CIR estimation, and tooutput a CIR corresponding to a result of the CIR estimation. Here, theCIR estimator scans the correlation signal with a first window and asecond window adjacent to the first window, calculates a ratio betweenan average power of the first window and an average power of the secondwindow, compares the calculated average power ratio with at least onethreshold value, and detects a start point, at which the average powerratio is initially equal to the at least one threshold value, and an endpoint, at which the average power ratio is lastly equal to the at leastone threshold value so as to detect a CIR distribution area; eliminatesthe noise from the CIR distribution area; and estimates the CIR.

The CIR estimator may scan the first window and the second window by apredetermined step interval repeatedly; calculate a first ratio of theaverage power of the second window to the average power of the firstwindow and a second ratio of the average power of the first window tothe average power of the second window according to corresponding step;compare the first ratio with a first threshold value to detect the startpoint, at which the first ratio is initially equal to the firstthreshold value, based on a result of the comparison; and compare thesecond ratio with a second threshold value to detect the end point, atwhich the second ratio is lastly equal to the second threshold value,based on a result of the comparison.

The first ratio may have characteristics of F distribution, the firstthreshold value may correspond to a value corresponding to F_(β)(D_(l),D_(r)) in an F distribution table, the second ratio may have thecharacteristics of the F distribution, the second threshold value maycorrespond to a value corresponding to F_(β)(D_(r), D_(l)) in the Fdistribution table. Here, β is be a false detection probability, D_(l)is a length of the first window, and D_(r) is a length of the secondwindow.

The channel estimation apparatus may further include a PN removerconfigured to receive the baseband sampled complex signal and the CIR,to eliminate a frame head from the baseband sampled complex signal, torestore cyclic convolution relation between frame body data of thebaseband sampled complex signal and a current channel CIR, and to outputa restored frame body; a fast Fourier transform unit configured toperform fast Fourier transform of the restored frame body and to outputa fast Fourier transformed signal; a discrete Fourier transform unitconfigured to receive the CIR, to perform discrete Fourier transform ofthe CIR, and to output a discrete Fourier transformed signal; and achannel equalizer configured to perform channel equalization based onthe fast Fourier transformed signal and the discrete Fourier transformedsignal and to output an equalized signal.

The channel estimation apparatus may further include a decoderconfigured to receive the equalized signal output from the channelequalizer, to perform channel decoding on the equalized signal, and tooutput a decoded signal.

The channel estimation apparatus may be implemented in an orthogonalfrequency division multiplexing (OFDM) receiver.

According to further embodiments of the present invention, a channelestimation apparatus includes a channel estimator configured to receivea fast Fourier transformed baseband sampled complex signal and a pilotfrequency, to detect a magnitude of the fast Fourier transformedbaseband sampled complex signal according to the pilot frequency, and tocalculate channel gains corresponding to a result of the detection; aninterpolator configured to receive the channel gains, to perform inversediscrete Fourier transform of the channel gains, to scan an inversediscrete Fourier transformed signal with a first window and a secondwindow adjacent to the first window, to calculate a ratio between anaverage power of the first window and an average power of the secondwindow, to compare the calculated average power ratio with at least onethreshold value, to detect a start point, at which the average powerratio is initially equal to the at least one threshold value, and an endpoint, at which the average power ratio is lastly equal to the at leastone threshold value so as to detect a CIR distribution area, toeliminate noise from the CIR distribution area, to estimate CIRinformation, to perform discrete Fourier transform of the CIRinformation, and to output a discrete Fourier transformed signal; and achannel equalizer configured to perform channel equalization based onthe fast Fourier transformed baseband sampled complex signal and thediscrete Fourier transformed signal output from the interpolator and tooutput an equalized signal.

The interpolator may scan the first window and the second window by apredetermined step interval repeatedly; calculate a first ratio of theaverage power of the second window to the average power of the firstwindow and a second ratio of the average power of the first window tothe average power of the second window according to corresponding step;compare the first ratio with a first threshold value to detect the startpoint, at which the first ratio is initially equal to the firstthreshold value, based on a result of the comparison; and compare thesecond ratio with a second threshold value to detect the end point, atwhich the second ratio is lastly equal to the second threshold value,based on a result of the comparison.

The first ratio may have characteristics of F distribution, the firstthreshold value may correspond to a value corresponding to F_(β)(D_(l),D_(r)) in an F distribution tables the second ratio may have thecharacteristics of the F distribution, the second threshold value maycorrespond to a value corresponding to F_(β)(D_(r), D_(l)) in the Fdistribution table. Here, β is be a false detection probability, D_(l)is a length of the first window, and D_(r) is a length of the secondwindow.

The interpolator may include an inverse discrete Fourier transform unitconfigured to receive the channel gains, to perform inverse discreteFourier transform of the channel gains, and to output inverse discreteFourier transformed signals; a CIR estimator configured to receive theinverse discrete Fourier transformed signals, to eliminate channel noisefrom the inverse discrete Fourier transformed signals, to perform CIRestimation, and to output a CIR corresponding to a result of the CIRestimation; and a discrete Fourier transform unit configured to receivethe estimated CIR, to perform discrete Fourier transform of the CIR, andto output the discrete Fourier transformed signal.

The channel estimation apparatus may further include a fast Fouriertransform unit configured to receive a baseband sampled complex signal,to perform fast Fourier transform of the baseband sampled complexsignal, and to output the fast Fourier transformed baseband sampledcomplex signal.

The channel estimation apparatus may further include a decoderconfigured to receive the equalized signal output from the channelequalizer, to perform channel decoding on the equalized signal, and tooutput a decoded signal.

The channel estimation apparatus may be implemented in an OFDM receiver.

The present invention will be described more fully hereinafter withreference to the accompanying drawings, in which embodiments of theinvention are shown. This invention may, however, be embodied in manydifferent forms and should not be construed as limited to the exemplaryembodiments set forth herein. Rather, these exemplary embodiments areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the invention to those skilled in the art.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are only used to distinguish oneelement from another. For example, a first signal could be termed asecond signal, and, similarly, a second signal could be termed a firstsignal without departing from the teachings of the disclosure.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” or “includes” and/or “including” when used in thisspecification, specify the presence of stated features, regions,integers, steps, operations, elements, and/or components, but do notpreclude the presence or addition of one or more other features,regions, integers, steps, operations, elements, components, and/orgroups thereof.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this invention belongs. It will befurther understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art and/orthe present application, and will not be interpreted in an idealized oroverly formal sense unless expressly so defined herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other features and advantages of the present inventionwill become more apparent by describing in detail exemplary embodimentsthereof with reference to the attached drawings in which like numbersrefer to like elements, and:

FIGS. 1A through 1C are graphs illustrating received OFDM (orthogonalfrequency division multiplexing) signals including noise and channelimpulse response (CIR) information;

FIG. 2 is a functional block diagram of a channel estimation apparatusin an OFDM receiver, according to an exemplary embodiment of the presentinvention;

FIG. 3 is a graph illustrating a signal R(n) input into the CIRestimator 30 included in the channel estimation apparatus 10 illustratedin FIG. 2;

FIG. 4 is a graph illustrating the CIR area detecting operationperformed by the CIR estimator 30 included in the channel estimationapparatus 10 illustrated in FIG. 2, according to some embodiments of thepresent invention;

FIG. 5 is a graph illustrating the CIR area detecting operationperformed by the CIR estimator 30 included in the channel estimationapparatus 10 illustrated in FIG. 2, according to other embodiments ofthe present invention;

FIG. 6 is a functional block diagram of a channel estimation apparatus100, according to another embodiment of the present invention;

FIG. 7 is a flowchart of a channel estimation method according to someembodiments of the present invention;

FIG. 8 is a graph illustrating a symbol error rate (SER) resulting froma channel estimation method, according to some embodiments of thepresent invention; and

FIG. 9 is a graph illustrating an SER resulting from a channelestimation method, according to other embodiments of the presentinvention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS OF THE INVENTION

FIG. 2 is a functional block diagram of a channel estimation apparatus(or of an orthogonal frequency division multiplexing (OFDM) receiverincluding such a channel estimation apparatus) 10, according to anexemplary embodiment of the present invention. FIG. 3 is a graphillustrating a signal input into the channel impulse response (CIR)estimator 30 included in the channel estimation apparatus 10 illustratedin FIG. 2. FIGS. 4 and 5 are graphs illustrating the CIR area detectingoperation performed by the CIR estimator 30 included in the channelestimation apparatus 10 illustrated in FIG. 2, according to alternativeembodiments of the present invention.

Referring to FIGS. 2 through 5, a channel estimation apparatus 10includes a correlator 20, a CIR estimator 30, a pseudo-noise (PN)remover 40, a fast Fourier transform (FFT) unit 50, a discrete Fouriertransform (DFT) unit 60, a channel equalizer 70, and a decoder 80. Thechannel estimation apparatus 10 may be implemented in an OFDM receiver,and particularly, in a time domain synchronous (TDS)-OFDM receiver.

The correlator 20 receives a baseband sampled complex signal S1 and alocally stored PN signal and calculates the correlation between the twosignals so as to generate a correlation signal R(n). Since a frame headof the baseband sampled complex signal S1 is known PN data for use inthe channel estimation apparatus 10, the baseband sampled complex signalS1 is correlated with the locally stored PN signal. This correlation maybe linear correlation or cyclic correlation and the correlation signalR(n) may include noise (e.g., correlation noise).

The CIR estimator 30 receives the correlation signal R(n), eliminatesnoise from the correlation signal R(n), estimates a CIR, and outputs afirst CIR (C1) corresponding to the estimation result. The first CIR(C1) is a noise-eliminated CIR signal. The CIR estimator 30 estimatesthe CIR based on two adjacent windows.

Referring to FIG. 3. in addition to a CIR correlation peak (CCP) whichincludes CIR information, noise like white Gaussian noise (i.e.,interference) is included in the correlation signal R(n). In order todetect a CIR distribution area from the correlation signal R(n), the CIRestimator 30 sets a first window W_(l) and a second window W_(r)adjacent to the first window W_(l), as illustrated in FIG. 4,continuously shifts (hereinafter, referred to as “scans”) the firstwindow W_(l) and the second window W_(r) by a predetermined step (timeinterval) with respect to the correlation signal R(n), and calculatesthe ratio between average power of the first window W_(l) and theaverage power of the second window W_(r). The predetermined step (timeinterval) is a scan interval at which the first window W_(l) and thesecond window W_(r) are scanned along the time axis, i.e., the timeindex in FIG. 4.

When the average power of the first window W_(l) is represented byE_(l)(p) and the average power of the second window W_(r) is representedby E_(r)(p), E_(l)(p) and E_(r)(p) can be calculated using Equation (1):

$\begin{matrix}{{{E_{l}(p)} = {\left. {\frac{1}{D_{l}}{\sum\limits_{n = {p - D_{l}}}^{p - 1}{R(n)}^{2}}} \middle| {E_{r}(p)} \right. = \left. {\frac{1}{D_{r}}{\sum\limits_{n = p}^{p + D_{p} - 1}{R(n)}^{2}}} \right|}},} & (1)\end{matrix}$

where p is a border value between the first window W_(l) and the secondwindow W_(r), D_(l) is the length of the first window W_(l), and D_(r)is the length of the second window W_(r). For instance, scanning isperformed by repeatedly adding the predetermined step interval (e.g., 10time units) to the border value p and the CIR estimator 30 calculatesthe ratio (average power ratio) between the average power of the firstwindow W_(l) and the average power of the second window W_(r) each timewhen the predetermined step interval is added.

The CIR estimator 30 compares the calculated average power ratio with atleast one threshold value, detects a start point Pa at which time theaverage power ratio is initially equal to the at least one thresholdvalue and an end point Pd, at which time the average power ratio is lastequal to the at least one threshold value so as to detect a CIRdistribution area LS, eliminates the noises i.e., interference in theCIR distribution LS, and estimates the CIR.

One threshold value or two different threshold values may be used. Forinstance, the CIR estimator 30 scans the first window W_(l) and thesecond window W_(r) by the predetermined step interval and calculates afirst ratio L1 (of the average power of the second window W_(r) to theaverage power of the first window W_(l)) and a second ratio L2 (of theaverage power of the first window W_(l) to the average power of thesecond window W_(r)). Thereafter, the CIR estimator 30 compares thefirst ratio L1 with a first threshold value (not shown) and detects thestart point Pa, at which the first ratio L1 is initially equal to thefirst threshold value. In addition, the CIR estimator 30 compares thesecond ratio L2 with a second threshold value (not shown) and detectsthe end point Pd, at which the second ratio L2 is lastly equal to thesecond threshold value.

The first ratio L1 may have the characteristics of the F distributionand the first threshold value may correspond to a value corresponding toF_(β)(D_(l), D_(r)) in an F distribution table. In addition, the secondratio L2 may have the characteristics of the F distribution and thesecond threshold value may correspond to a value corresponding toF_(β)(D_(r), D_(l)) in the F distribution table. Here, β is a falsedetection probability. The characteristics of the F distribution and theF distribution table are disclosed in “J. S. Milton and J. C. Arnold,“Introduction to Probability and Statistics: Principles and Applicationsfor Engineering and the Computer Sciences,” 4th ed., New York,McGraw-Hill, 2000”.

The CIR estimator 30 may eliminate the interference included within theCIR distribution area LS using a threshold detection method and estimatethe CIR C1. For instance, the CIR estimator 30 sets a threshold valuehaving a magnitude corresponding to 1/m or 1/n (where each of “m” and“n” are a natural number, e.g., 4) of the magnitude of the CCP includingthe CIR information in the detected CIR distribution area LS. The CIRestimator 30 detects signals having a magnitude greater than thethreshold value, and eliminates the detected signals from thecorrelation signal R(n), thereby eliminating the interference.

According to some embodiments of the present invention, beforeestimating the CIR information, the CIR estimator 30 narrows a rangesubjected to the threshold detection by setting the CIR distributionarea LS and eliminates the interference from the CIR distribution areaLS, so that false detection of the CIR information can be prevented.

The CIR estimator 30 eliminates noise using the threshold detectionmethod and then estimates the CIR information. Thereafter, the CIRestimator 30 sets the CIR distribution area LS using the two adjacentwindows, eliminates interference using the threshold detection methodagain, and estimates the CIR C1. In this manner, noise that may beincluded in the CIR C1 can be completely eliminated.

The PN remover 40 receives the baseband sampled complex signal S1 andthe CIR C1, eliminates the frame head (PN data) from the basebandsampled complex signal S1, restores the cyclic convolution relationbetween frame body data of the baseband sampled complex signal S1 and acurrent channel CIR, and outputs a restored frame body S3.

The FFT unit 50 performs FFT of the restored frame body S3 and outputs afast Fourier transformed (FFT'ed) signal S5. The DFT unit 60 receivesthe CIR C1 and performs DFT of the CIR C1 so as to output a discreteFourier transformed (DFT'ed) signal C3. The channel equalizer 70performs channel equalization based on the FFT'ed signal S5 and theDFT'ed signal C3 and outputs an equalized signal D1. The decoder 80 maybe referred to as a forward error control (FEC) device. The decoder 80receives the equalized signal D1 output from the channel equalizer 70and performs channel decoding on it so as to output a decoded signal(i.e., an output decoded bit stream, ODB).

FIG. 6 is a functional block diagram of a channel estimation apparatus(or an OFDM receiver including the channel estimation apparatus) 100,according to another embodiment of the present invention. Referring toFIG. 6, the channel estimation apparatus 100 includes an FFT unit 110, achannel estimator 120, an interpolator 130, a channel equalizer 140, anda decoder 150. The channel estimation apparatus 100 may be implementedin an OFDM receiver or in a CP-OFDM receiver.

The FFT unit 110 receives a baseband sampled complex signal B1 andperforms FFT of it so as to output an FFT'ed signal B3. The channelestimator 120 detects the magnitude of the FFT'ed baseband sampledcomplex signal B3 according to a pilot frequency PF and calculateschannel gains B5 corresponding to a result of the detection. Each of thechannel gains B5 may be calculated using a least square (LS) method or aminimum mean-square error (MMSE) method.

The interpolator 130 receives the channel gains B5, performs inverse DFT(IDFT) of them, eliminates noise from an inverse discrete Fouriertransformed (IDFT'ed) signal B7 based on two adjacent windows, estimatesa noise-eliminated CIR signal, i.e., a CIR B9, and performs DFT of theCIR B9 so as to output a DFT'ed signal B11. The interpolator 130includes an IDFT unit 132, a CIR estimator 134, and a DFT unit 136.

The IDFT unit 132 receives the channel gains BS and performs IDFT ofthem so as to output the IDTF'ed signal B7. The CIR estimator 134receives the IDFT'ed signal B7, eliminates noise from the IDFT'ed signalB7, performs CIR estimation, and outputs the CIR B9 corresponding to aresult of the CIR estimation.

The channel noise elimination and the CIR estimation are performed bychannel estimation (134) based on two adjacent windows, which has beendescribed above with reference to the CIR estimator 30 shown in FIG. 2.The CIR estimator 134 has almost the same functions as the CIR estimator30 shown in FIG. 2, with the exception that the CIR estimator 134performs channel noise elimination and CIR estimation based on theIDFT'ed signal B7 instead of the correlation signal R(n) and outputs theCIR B9 corresponding to a result of the CIR estimation. Thus, a detaileddescription thereof will be omitted.

The DFT unit 136 receives the CIR B9 and performs DFT of it so as tooutput the DFT ed signal B11.

The channel equalizer 140 performs channel equalization based on theFFT'ed baseband sampled complex signal B3 and the DFT'ed signal B11 andoutputs an equalized signal B13. The decoder 150 receives the equalizedsignal B13 output from the channel equalizer 140 and performs channeldecoding on the equalized signal B13 so as to output an ODB signal.

FIG. 7 is a flowchart of a channel estimation method according to someembodiments of the present invention, Referring to FIGS. 2 through 7, instep S100, the CIR estimator 30 or 134 eliminates noise from thecorrelation signal R(n) generated by the correlator 20 illustrated inFIG. 2 or from the IDFT'ed signal B7 generated by the IDFT unit 132,performs CIR estimation, and outputs a first CIR corresponding to aresult of the CIR estimation. In step S110, the CIR estimator 30 (FIG.2) or 134 (FIG. 6) sets the first window W and the second window W_(r)(adjacent to the first window W_(l)) based on the first CIR. In stepS120, the CIR estimator 30 or 134 continuously scans the first windowW_(l) and the second window W_(r) by a predetermined step interval andcalculates the average power of the first window W_(l) and the averagepower of the second window W_(r) according to the corresponding stepinterval. In step S130, the CIR estimator 30 or 134 calculates the firstratio L1 (ratio of the average power of the second window W_(r) to theaverage power of the first window W_(l)) and the second ratio L2 (ratioof the average power of the first window W_(l) to the average power ofthe second window W_(r)). In step S140, the CIR estimator 30 or 134compares the first ratio L1 with a first threshold value, and detectsthe start point Pa at which the first ratio L1 is initially equal to thefirst threshold value based on a result of the comparison. In step S150,the CIR estimator 30 or 134 compares the second ratio L2 with a secondthreshold value, and detects the end point Pd at which the second ratioL2 is last equal to the second threshold value based on a result of thecomparison. In step S160, the CIR estimator 30 or 134 detects orcalculates the CIR distribution area LS based on the start point Pa andthe end point Pd. In step S170, the CIR estimator 30 or 134 eliminatesnoise from the first CIR and performs CIR estimation, with respect tothe CIR distribution area LS, so as to output a second CIR.

In other words, after first CIR estimation, CIR estimation is morefinely performed by scanning the first window W_(l) and the secondwindow W_(r) so that noise interference can be minimized and accuratechannel estimation can be accomplished.

FIGS. 8 and 9 are graphs illustrating a measured symbol error rate (SER)resulting from a channel estimation method according to an embodiment ofthe present invention. FIG. 8 illustrates the result of simulating afixed reception F1 version of a digital video broadcasting (DVB)-Tchannel model, which is disclosed in “DVB: Frame Structure ChannelCoding and Modulation for Digital Terrestrial Television. ETSI, Tech.Rep. EN300 744 v1.1.2. August 1997”, on the conditions that both of thelength D_(l) of the first window W_(l) and the length D_(r) of thesecond window W_(r) were 25, the start point Pa and the end point Pd ofthe CIR distribution area were 6, the length LS of the CIR distributionarea was 120, a step size was 10, and the false detection probability βwas 0.1%. Referring to FIG. 8, a measured SER indicated by LCIC+MWPRobtained when a channel estimation method according to some embodimentof the present invention was used, is almost identical to thatcalculated for an ideal CIR. Accordingly, it can be inferred that ansymbol error rate can be reduced in an actual OFDM system performing achannel estimation method according to an embodiment of the presentinvention.

FIG. 9 illustrates the SER resulting from the disclosed channelestimation method, in a simulated TU6 channel models which is disclosedin “COST 207 TD(86)51-REW 3(WG1); Proposal on Channel Transfer Functionsto be Used in GSM Tests Late 1986, September 1986”, under the sameconditions as in the simulation described in FIG. 8. Referring to FIG.9, a measured SER, which is indicated by LCIC+MWPR obtained when achannel estimation method according to some embodiment of the presentinvention is used, is almost identical to that obtained in an ideal CIR.Accordingly, it can be inferred that an error rate can be reduced in anactual OFDM system performing a channel estimation method according toan embodiment of the present invention.

Embodiments of the invention can also be implemented as computerreadable codes on a computer readable recording medium. The computerreadable recording medium may be any data storage device that can storedata which can thereafter be read (and executed) by a computer system.The computer readable recording medium can also be distributed overnetwork coupled computer systems so that the computer readable code isstored and executed in a distributed fashion. Also, functional programscodes and code segments for accomplishing the method of the presentinvention can be easily constructed by programmers skilled in the art towhich the present invention pertains.

As described above, according to some embodiments of the presentinvention, a CIR distribution area is subdivided (dynamically during CIRestimation) and noise interference is minimized, so that accuratechannel estimation can be accomplished.

While the present invention has been shown and described with referenceto exemplary embodiments thereof, it will be understood by those ofordinary skill in the art that various changes in form and detail may bemade herein without departing from the spirit and scope of the presentinvention, as defined by the following claims.

1. A channel estimation method comprising: detecting a channel impulseresponse (CIR) distribution area by scanning a signal containing noiseand CIR information with a first window and a second window.
 2. Thechannel estimation method of claim 1, wherein the second window isadjacent to the first window and wherein detecting the CIR distributionarea further comprises: calculating a average power of the signal withinthe first window and a average power of the signal within the secondwindow; determining a start point of the channel impulse response (CIR)distribution area using the average power of the signal within the firstwindow and the average power of the signal within the second window; anddetermining an end point of the channel impulse response (CIR)distribution area using the average power of the signal within the firstwindow and the average power of the signal within the second window. 3.The channel estimation method of claim 2, wherein detecting the CIRdistribution area further comprises: calculating the ratio between theaverage power of the signal within the first window and the averagepower of the signal within the second window; comparing the ratio ofcalculated averages with at least one threshold value; and determiningthe start point as the point at which the average power ratio isinitially equal to the at least one threshold value; determining the endpoint as the point at which the average power ratio is lastly equal tothe at least one threshold value
 4. The channel estimation method ofclaim 3, wherein detecting the CIR distribution area comprises: scanningthe first window and the second window by a predetermined step intervalrepeatedly and calculating the average power of the signal within thefirst window and the average power of the signal within the secondwindow; calculating a first ratio of the average power of the signalwithin the second window to the average power of the signal within thefirst window; calculating a second ratio of the average power of thesignal within the first window to the average power of the signal withinthe second window; detecting the start point by comparing the firstratio with a first threshold value and; and detecting the end point bycomparing the second ratio with a second threshold value.
 5. The channelestimation method of claim 4, wherein the first ratio hascharacteristics of F distribution, the first threshold value correspondsto a value corresponding to F_(β)(D_(l), D_(r)) in an F distributiontable, wherein the second ratio has the characteristics of the Fdistribution, the a second threshold value corresponds to a valuecorresponding to F_(β)(D_(r), D_(l)) in the F distribution table, β is afalse detection probability, D_(l) is a length of the first window, andD_(r) is a length of the second window.
 6. The channel estimation methodof claim 3, further comprising, after detecting the CIR distributionarea, eliminating the noise from the CIR distribution area andestimating the CIR information.
 7. The channel estimation method ofclaim 3, further comprising, before detecting the CIR distribution area,eliminating other noise from the signal and estimating the CIRinformation.
 8. A computer readable recording medium for recording aprogram for executing the channel estimation method of claim
 1. 9. Achannel estimation apparatus comprising: a linear correlator configuredto receive a baseband sampled complex signal and a locally storedpseudo-noise (PN) signal and to generate a correlation signal bycalculating a linear correlation between received signals; and a channelimpulse response (CIR) estimator configured to receive the correlationsignal, to eliminate noise from the correlation signal, to perform CIRestimation, and to output a CIR corresponding to a result of the CIRestimation; wherein the CIR estimator: scans the correlation signal witha first window and a second window adjacent to the first window,calculates the average power of the signal within the first window andthe average power of the signal within the second window; determines astart point of a channel impulse response (CIR) distribution area usingthe average power of the signal within the first window and the averagepower of the signal within the second window; and determines an endpoint of the channel impulse response (CIR) distribution area using theaverage power of the signal within the first window and the averagepower of the signal within the second window.
 10. The channel estimationapparatus of claim 9, wherein the CIR estimator: calculates a ratiobetween an average power of the first window and an average power of thesecond window, compares the calculated average power ratio with at leastone threshold value, and detects a start point, at which the averagepower ratio is initially equal to the at least one threshold value, andan end point, at which the average power ratio is lastly equal to the atleast one threshold value so as to detect the CIR distribution area;eliminates the noise from the CIR distribution area; and estimates theCIR.
 11. The channel estimation apparatus of claim 9, wherein the CIRestimator: scans the first window and the second window shifted by apredetermined step interval repeatedly; calculates a first ratio of theaverage power of the second window to the average power of the firstwindow and a second ratio of the average power of the first window tothe average power of the second window; compares the first ratio with afirst threshold value to detect the start point at which the first ratiois initially equal to the first threshold value; and compares the secondratio with a second threshold value to detect the end point, at whichthe second ratio is lastly equal to the second threshold value.
 12. Thechannel estimation apparatus of claim 11, wherein the first ratio hascharacteristics of F distribution, the first threshold value correspondsto a value corresponding to F_(β)(D_(l), D_(r)) in an F distributiontable, the second ratio has the characteristics of the F distribution,the second threshold value corresponds to a value corresponding toF_(β)(D_(r), D_(l)) in the F distribution table, β is a false detectionprobability, D_(l) is a length of the first window, and D_(r) is alength of the second window.
 13. The channel estimation apparatus ofclaim 9, further comprising: a PN remover configured to receive thebaseband sampled complex signal and the CIR, to eliminate a frame headfrom the baseband sampled complex signal, to restore cyclic convolutionrelation between frame body data of the baseband sampled complex signaland a current channel CIR, and to output a restored frame body; a fastFourier transform unit configured to perform fast Fourier transform ofthe restored frame body and to output a fast Fourier transformed signal;a discrete Fourier transform unit configured to receive the CIR, toperform discrete Fourier transform of the CIR, and to output a discreteFourier transformed signal; and a channel equalizer configured toperform channel equalization based on the fast Fourier transformedsignal and the discrete Fourier transformed signal and to output anequalized signal.
 14. The channel estimation apparatus of claim 9,further comprising a decoder configured to receive the equalized signaloutput from the channel equalizer, to perform channel decoding on theequalized signal, and to output a decoded signal.
 15. The channelestimation apparatus of claim 9, wherein the channel estimationapparatus is implemented in an orthogonal frequency divisionmultiplexing (OFDM) receiver.
 16. A channel estimation apparatuscomprising a channel estimator configured to: receive a fast Fouriertransformed baseband sampled complex signal and a pilot frequency;detect a magnitude of the fast Fourier transformed baseband sampledcomplex signal according to the pilot frequency; and calculate channelgains corresponding to a result of the detection; an interpolatorconfigured to: receive the channel gains; perform inverse discreteFourier transform of the channel gains; scan an inverse discrete Fouriertransformed signal within a first window and within a second windowadjacent to the first window; and calculate the average power of thesignal within the first window and the average power of the signalwithin the second window; detect a start point and an end point of achannel impulse response (CIR) distribution area based on the averagepower of the signal within the first window and the average power of thesignal within the second window; eliminate noise from the CIRdistribution area; estimate CIR information within the channel impulseresponse (CIR) distribution area; perform discrete Fourier transform ofthe CIR information, and output a discrete Fourier transformed signal;and a channel equalizer configured to perform channel equalization basedon the fast Fourier transformed baseband sampled complex signal and thediscrete Fourier transformed signal output from the interpolator and tooutput an equalized signal.
 17. The channel estimation apparatus ofclaim 16, wherein the interpolator is configured to detect the startpoint of the channel impulse response (CIR) distribution area by:calculating the ratio between the average power of the signal within thefirst window and the average power of the signal within the secondwindow; comparing calculated ratio with at least one threshold value;and determining the start point as the point at which the average powerratio is initially equal to the at least one threshold value.
 18. Thechannel estimation apparatus of claim 16, wherein the interpolator isconfigured detect the end point of the channel impulse response (CIR)distribution area by: calculating the ratio between the average power ofthe signal within the first window and the average power of the signalwithin the second window; comparing calculated ratio with at least onethreshold value; and determining the end point as the point at which theaverage power ratio is lastly equal to the at least one threshold value.19. The channel estimation apparatus of claim 16, wherein theinterpolator: scans the first window and the second window by apredetermined step interval repeatedly; calculates a first ratio of theaverage power of the signal within the second window to the averagepower of the signal within the first window and a second ratio of theaverage power of the signal within the first window to the average powerof the signal within the second window; compares the first ratio with afirst threshold value to detect the start point as the point at whichthe first ratio is initially equal to the first threshold value; andcompares the second ratio with a second threshold value to detect theend point as the point at which the second ratio is lastly equal to thesecond threshold value.
 20. The channel estimation apparatus of claim19, wherein the first ratio has characteristics of F distribution, thefirst threshold value corresponds to a value corresponding toF_(β)(D_(l), D_(r)) in an F distribution table, the second ratio has thecharacteristics of the F distribution, the second threshold valuecorresponds to a value corresponding to F_(β)(D_(r), D_(l)) in the Fdistribution table, β is a false detection probability, D_(l) is alength of the first window, and D_(r) is a length of the second window.21. The channel estimation apparatus of claim 16, wherein theinterpolator comprises: an inverse discrete Fourier transform unitconfigured to receive the channel gains, to perform inverse discreteFourier transform of the channel gains, and to output inverse discreteFourier transformed signals; a CIR estimator configured to receive theinverse discrete Fourier transformed signals, to eliminate channel noisefrom the inverse discrete Fourier transformed signals, to perform CIRestimation, and to output a CIR corresponding to a result of the CIRestimation; and a discrete Fourier transform unit configured to receivethe estimated CIR, to perform discrete Fourier transform of the CIR, andto output the discrete Fourier transformed signal.
 22. The channelestimation apparatus of claim 16, wherein the channel estimationapparatus is implemented in an orthogonal frequency divisionmultiplexing (OFDM) receiver.